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Related Experiment Videos

Robust fast controller design via nonlinear fractional differential equations.

Xi Zhou1, Yiheng Wei1, Shu Liang1

  • 1Department of Automation, University of Science and Technology of China, Hefei 230027, China.

ISA Transactions
|April 9, 2017
PubMed
Summary

A novel nonlinear fractional order controller enhances linear systems by improving response speed while maintaining robustness against parameter changes. This method ensures system stability and performance under perturbation.

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Area of Science:

  • Control Engineering
  • Nonlinear Systems Theory
  • Fractional Order Systems

Background:

  • Linear systems control design often faces trade-offs between robustness and response speed.
  • Achieving desired damping ratios under parameter perturbations while improving rise time is a significant challenge.

Purpose of the Study:

  • To propose a new method for linear system controller design.
  • To develop a novel nonlinear fractional order controller that achieves both robustness and fast response.
  • To provide theoretical guarantees and practical design guidelines for the proposed controller.

Main Methods:

  • Exploiting techniques from nonlinear systems control and fractional order systems control.
  • Deriving a novel nonlinear fractional order controller.
Keywords:
Fast responseFractional order systemsNonlinear controlRobustness

Related Experiment Videos

  • Developing two comparison theorems for analyzing fractional differential equations.
  • Estimating the rise time of the closed-loop system.

    • Main Results:

    • The proposed controller ensures the damping ratio remains at its desired value despite system parameter perturbations.
    • The controller design allows for tuning to improve the system's rise time (fast response).
    • Theoretical analysis using comparison theorems validates the closed-loop system performance.
    • Numerical examples demonstrate the effectiveness of the developed method.

    Conclusions:

    • The novel nonlinear fractional order controller effectively balances robustness and fast response in linear systems.
    • The theoretical framework and estimation techniques facilitate practical controller design.
    • The method offers a promising approach for enhancing control system performance in the presence of uncertainties.